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Multi-focus image fusion using PCNN

Authors :
Wang, Zhaobin
Ma, Yide
Gu, Jason
Source :
Pattern Recognition. Jun2010, Vol. 43 Issue 6, p2003-2016. 14p.
Publication Year :
2010

Abstract

Abstract: This paper proposes a new method for multi-focus image fusion based on dual-channel pulse coupled neural networks (dual-channel PCNN). Compared with previous methods, our method does not decompose the input source images and need not employ more PCNNs or other algorithms such as DWT. This method employs the dual-channel PCNN to implement multi-focus image fusion. Two parallel source images are directly input into PCNN. Meanwhile focus measure is carried out for source images. According to results of focus measure, weighted coefficients are automatically adjusted. The rule of auto-adjusting depends on the specific transformation. Input images are combined in the dual-channel PCNN. Four group experiments are designed to testify the performance of the proposed method. Several existing methods are compared with our method. Experimental results show our presented method outperforms existing methods, in both visual effect and objective evaluation criteria. Finally, some practical applications are given further. [Copyright &y& Elsevier]

Details

Language :
English
ISSN :
00313203
Volume :
43
Issue :
6
Database :
Academic Search Index
Journal :
Pattern Recognition
Publication Type :
Academic Journal
Accession number :
48255498
Full Text :
https://doi.org/10.1016/j.patcog.2010.01.011